The design of radio-frequency power amplifiers for communications applications often involves a trade-off between linearity and efficiency. Power amplifiers are typically most efficient when operated at or near the saturation point. However, the response of the amplifier at or near the point of saturation is non-linear. Generally speaking, when operating in the high-efficiency range, a power amplifier's response exhibits nonlinear and memory effects.
One way to improve a power amplifier's efficiency and its overall linearity is to digitally pre-distort the input to the power amplifier to compensate for the distortion introduced by the power amplifier. In effect, the input signal is adjusted in anticipation of the distortion to be introduced by the power amplifier, so that the output signal is largely free of distortion products. Adaptive digital predistortion is a proven technology that can achieve high linearity and efficiency in power amplifiers. Generally, an adaptive digital predistorter is implemented based on a behavior model. The behavior model can be adapted by an adaptation circuit to model the distortions introduced by a particular power amplifier.
Two types of behavior models are commonly used in digital predistorters. One type of behavior models is neural network based and the other is polynomial function based. In a polynomial function based behavior model (referred to as “PF model” hereafter) a non-linear function is represented by a weighted sum of collection of basis functions. The collection of basis functions may be a set of power series functions or a set of orthogonal basis functions. In the present application, for notational simplicity, a behavior model based on a set of power series functions is referred to as a PSF model and a behavior model based on a set of orthogonal basis functions is referred to as an OBF model. A non-linear function can also be implemented by a look-up table. A behavior model for a digital predistorter based on look-up tables is referred to as a LUT model hereafter.
An adaptive digital predistorter can be implemented based on any one of the three models, PSF, OBF and LUT. However, the complexity of the adaptive digital predistorter varies depending on the model used. As an adaptive digital predistorter needs to be adapted or trained for a particular power amplifier by an adaptation circuit, the complexity of the adaptation circuit depends on the model as well.
Besides complexity, other factors, such as costs, stability, dynamic range, are also important in selecting a model for both predistorter circuit and adaptation circuit. When the model selected for a predistorter circuit is different from the model selected for an adaptation circuit, conversion techniques are required to convert model coefficients trained in the adaptation circuit to coefficients suitable for the predistorter circuit model.